Industry Challenge/ Challenges
Businesses generate massive amounts of data that must be analyzed in order to derive business value. A carefully managed data pipeline needs to be built to provide organizations access to reliable and well-structured datasets for analytics.
But here are the few challenges that organizations face while managing huge amounts of data
- Volume
Organizations often have sprawling webs of data sources. Managing all these sources is a complex and time-consuming task
- Velocity
Organizations generate new data at a rapid speed and are usually required to analyze and respond in real-time.
- Variety
Identifying, understanding and classifying different types of data is a tedious task. Managing this data manually is a time-consuming affair.
Problem Statement
Create data pipelines for massive amounts of campaign performance data and build various web applications around the data pipelines, for user notifications, audience creation, etc
Our Solution
- For campaign performance data, we built a few ETL pipelines, data warehouses, and data lakes for platforms such as DV360, Adwords, Facebook, and Campaign Manager. In addition, Nifi, AWS Data Lake, and Spark were used to ingest terabytes of data for a variety of advertisers.
- Algoscale developed several Scala, Java, and Python backend applications to serve the ingested campaign data, ranging from batch to real-time, and utilizing a variety of technologies such as Kafka, Akka, Postgres, Elasticsearch, and others.
- The final step included deploying these applications using tools such as Docker, Kubernetes, and Jenkins.
Technology
Tech Stack
Business Impact
Our data pipelines have greatly aided business users in obtaining faster and more accurate reporting.
- We have successfully delivered numerous applications that are now an integral part of our client’s product.
- Processes about a terabyte of data on a daily basis
Also Read: Data Warehouse For Leading Conversational Messaging Platform
Campaign Data Integration & Analytics
